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All Journal Tekno : Jurnal Teknologi Elektro dan Kejuruan ELKHA : Jurnal Teknik Elektro Mechatronics, Electrical Power, and Vehicular Technology Jurnal Simetris Bulletin of Electrical Engineering and Informatics Jurnal Informatika Jurnal Ilmiah Teknik Elektro Komputer dan Informatika (JITEKI) Jurnal Pekommas Jurnal Teknologi Informasi dan Ilmu Komputer Jurnal Edukasi dan Penelitian Informatika (JEPIN) International Journal of Advances in Intelligent Informatics JURNAL NASIONAL TEKNIK ELEKTRO JOIV : International Journal on Informatics Visualization Al Ishlah Jurnal Pendidikan Sinkron : Jurnal dan Penelitian Teknik Informatika Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) International Journal of Artificial Intelligence Research JOURNAL OF INFORMATICS AND TELECOMMUNICATION ENGINEERING Knowledge Engineering and Data Science Kinetik: Game Technology, Information System, Computer Network, Computing, Electronics, and Control Jurnal Sains dan Informatika Pendas : Jurnah Ilmiah Pendidikan Dasar SELAPARANG: Jurnal Pengabdian Masyarakat Berkemajuan ILKOM Jurnal Ilmiah SENTIA 2017 SENTIA 2016 MATRIK : Jurnal Manajemen, Teknik Informatika, dan Rekayasa Komputer Lectura : Jurnal Pendidikan Prosiding SAKTI (Seminar Ilmu Komputer dan Teknologi Informasi) PEDULI: Jurnal Imiah Pengabdian Pada Masyarakat Infotekmesin Buletin Ilmiah Sarjana Teknik Elektro International Journal of Visual and Performing Arts Generation Journal Jurnal Mnemonic Frontier Energy System and Power Engineering Masyarakat Berdaya dan Inovasi SOSIOEDUKASI : JURNAL ILMIAH ILMU PENDIDIKAN DAN SOSIAL Community Development Journal: Jurnal Pengabdian Masyarakat Indonesian Journal of Data and Science Letters in Information Technology Education (LITE) Jurnal Graha Pengabdian Jurnal Abdimas Berdaya : Jurnal Pembelajaran, Pemberdayaan dan Pengabdian Masyarakat Science in Information Technology Letters International Journal of Engineering, Science and Information Technology International Journal of Robotics and Control Systems ALINIER: Journal of Artificial Intelligence & Applications Ilmu Komputer untuk Masyarakat SinarFe7 Jurnal Maklumatika Applied Engineering and Technology Jurnal Ekonomi, Bisnis dan Pendidikan (JEBP) Jurnal Inovasi Teknologi dan Edukasi Teknik PROSIDING SEMINAR NASIONAL PENELITIAN DAN PENGABDIAN KEPADA MASYARAKAT (SNPPM) UNIVERSITAS MUHAMMADIYAH METRO Bulletin of Social Informatics Theory and Application Karunia: Jurnal Hasil Pengabdian Masyarakat Indonesia Jurnal Informatika Polinema (JIP) ABDI UNISAP: Jurnal Pengabdian Kepada Masyarakat International Journal of Mechanical, Industrial and Control Systems Engineering Journal of Engineering and Technological Sciences Jurnal ilmiah teknologi informasi Asia Jurnal Elektronika dan Telekomunikasi
Anik Nur Handayani
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Classifying BISINDO Alphabet using TensorFlow Object Detection API Hayati, Lilis Nur; Handayani, Anik Nur; Irianto, Wahyu Sakti Gunawan; Asmara, Rosa Andrie; Indra, Dolly; Fahmi, Muhammad
ILKOM Jurnal Ilmiah Vol 15, No 2 (2023)
Publisher : Prodi Teknik Informatika FIK Universitas Muslim Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33096/ilkom.v15i2.1692.358-364

Abstract

Indonesian Sign Language (BISINDO) is one of the sign languages used in Indonesia. The process of classifying BISINDO can be done by utilizing advances in computer technology such as deep learning. The use of the BISINDO letter classification system with the application of the MobileNet V2 FPNLite  SSD model using the TensorFlow object detection API. The purpose of this study is to classify BISINDO letters A-Z and measure the accuracy, precision, recall, and cross-validation performance of the model. The dataset used was 4054 images with a size of  consisting of 26 letter classes, which were taken by researchers by applying several research scenarios and limitations. The steps carried out are: dividing the ratio of the simulation dataset 80:20, and applying cross-validation (k-fold = 5). In this study, a real time testing using 2 scenarios was conducted, namely testing with bright light conditions of 500 lux and dim light of 50 lux with an average processing time of 30 frames per second (fps). With a simulation data set ratio of 80:20, 5 iterations were performed, the first iteration yielded a precision result of 0.758 and a recall result of 0.790, and the second iteration yielded a precision result of 0.635 and a recall result of 0.77, then obtained an accuracy score of 0.712, the third iteration provides a recall score of 0.746, the fourth iteration obtains a precision score of 0.713 and a recall score of 0.751, the fifth iteration gives a precision score of 0.742 for a fit score case and the recall score is 0.773. So, the overall average precision score is 0.712 and the overall average recall score is 0.747, indicating that the model built performs very well.
CONVOLUTIONAL NEURAL NETWORK (CNN) UNTUK MENENTUKAN GAGRAK WAYANG KULIT Pratama, Awanda Setya Sanfajar; Prasetya Wibawa, Aji; Nur Handayani, Anik
Jurnal Mnemonic Vol 5 No 2 (2022): Mnemonic Vol. 5 No. 2
Publisher : Teknik Informatika, Institut Teknologi Nasional malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36040/mnemonic.v5i2.4671

Abstract

Indonesia adalah negara yang kaya akan keragaman budaya, salah satu dari budaya Indonesia adalah Wayang Kulit. Wayang kulit di Indonesia memiliki beragam gagrak, mulai dari Cirebon, Solo, Jawa-Timuran, Yogyakarta dan lain sebagainya. Keberagaman dari gagrak wayang kulit membuat generasi muda kesulitan untuk mengetahui gagrak dari wayang kulit. Dari permasalahan tersebut, peneliti akan mengembangkan sebuah machine learning dengan menggunakan Convolutional Neural Network (CNN) untuk menentukan gagrak wayang kulit. Tujuan penelitian ini adalah menghasilkan machine learning yang bisa menentukan gagrak dari wayang kulit. Data yang digunakan pada penelitian ini terdiri dari 280 gambar wayang kulit yang diunduh satu persatu di platform Facebook dan Google penelusuran gambar, warna latar belakang gambar tersebut diubah menjadi putih dan diubah ukuran menjadi 640*480 pixel. Data tersebut disebarkan melalui google form dan dilakukan validasi menggunakan Inter-annotator Agreement sehingga dapat digunakan pada proses pelatihan dengan metode CNN di Google Colab. Setelah itu dilakukan pengujian untuk menentukan gagrak wayang kulit menggunakan 3 arsitektur CNN yaang sudah dibuktikan pada penelitian-penelitian sebelumnya. Hasil dari penelitian ini menunjukan bahwa arsitektur yang digunakan oleh Sudiatmika & Dewi merupakan model klasifikasi terbaik dari ketiga arsitektur, arsitektur tersebut mendapatkan akurasi sebesar 92,27%, presisi sebesar 92,22%, recall sebesar 96,85% dan f-measure sebesar 91,93%.
PENGEMBANGAN ALAT PERAGA IOT MENGGUNAKAN MIKROKONTROLER NODEMCU ESP 8266 SEBAGAI MEDIA PEMBELAJARAN TEKNOLOGI INDUSTRI 4.0 SMK MUHAMMADIYAH 7 GONDANGLEGI Atmaja, Muhammad Bayu Setya Wahyu; Handayani, Anik Nur; Wirawan, I Made
TEKNO: Jurnal Teknologi Elektro dan Kejuruan Vol 33, No 1 (2023)
Publisher : Universitas Negeri Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.17977/um034v33i1p66-79

Abstract

Revolusi Industri 4.0 mempunyai dampak besar bagi berkembangnya sains dan teknologi, dimana teknologi dioperasikan untuk meminimalisir manusia dalam pengaplikasiannya demi ketepatan biaya, tenaga, waktu serta pemasukan informasi dalam waktu yang sama sesuai saat dibutuhkan melalui jaringan internet. Hasil wawancara dengan guru pengampu mata Pelajaran Instalasi Penerangan Listrik menunjukkan bahwa materi IoT masih baru dan belum ada media pembelajaran yang tersedia di kompetensi dasar teknologi IoT dalam mata pelajaran tersebut. Media pembelajaran yang dibutuhkan adalah jobsheet dan alat peraga sehingga perlu dikembangkan media pembelajaran yang sesuai dengan kompetensi dasar dan mata pelajaran yang ada. Penelitian dilakukan sesuai strategi Sugiyono dan dilaksanakan dalam beberapa langkah yaitu Potensi dan Masalah, Pengumpulan Data, Desain Produk, Validasi Desain, Revisi Desain, Uji Coba Produk, Revisi Produk, Uji Coba Pemakaian, Revisi Produk, dan Produksi. Penelitian dan pengembangan yang dilakukan telah menghasilkan produk berupa alat peraga dan jobsheet yang lolos uji kelayakan media belajar Revolusi Industri 4.0 yang menggunakan NodeMCU ESP 8266 12E. Hasil dari validitas produk yang dikembangkan memperoleh rata-rata validitas 89.06% untuk alat peraga dan 91.11% untuk jobsheet yang masuk pada kriteria sangat valid untuk alat peraga dan jobsheet. Kesimpulan dari penelitian ini, dari hasil rerata validasi dan uji coba jobsheet dan alat peraga yang telah dikembangkan, media pembelajaran tersebut layak dan dapat digunakan dalam kegiatan belajar dan pembelajaran Revolusi Industri ke 4.0.
PENGEMBANGAN E-MODUL INTERAKTIF PADA MATERI DAMPAK SOSIAL INFORMATIKA KELAS VII SMP Adi Prastowo, Nur Kodrad; Handayani, Anik Nur; Arif Widodo, Baskoro
Jurnal Inovasi Teknologi dan Edukasi Teknik Vol. 3 No. 12 (2023)
Publisher : Universitas Ngeri Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.17977/um068.v3.i12.2023.1

Abstract

Kegiatan pembelajaran di kelas acap terjadi peserta didik enggan mengikuti proses pembelajaran yang disampaikan oleh guru karena media yang digunakan tidak menarik bagi peserta didik.Penelitian ini bertujuan untuk mengembangkan e-modul interaktif yang berfokus pada materi dampak sosial informatika kelas vii SMP. Pengembangan E-modul Interaktif diharapkan dapat menjadi alternatif media pembelajaran menarik yang dapat membantu guru menyampaikan materi dengan lebih baik sehingga meningkatkan pemahaman peserta didik terhadap materi yang disampaikan dan memahami dampak sosial informatika dengan baik. E-modul interaktif ini diharapkan dapat memfasilitasi peserta didik untuk belajar secara mandiri, praktis dan efektif . Penelitian ini diharapkan dapat memberikan dampak positif bagi pendidikan dengan pemanfaatan teknologi guna meningkatkan minat belajar peserta didik.
Tinjauan Realitas Virtual dan Game Serius dalam Terapi Perilaku Kognitif untuk Gangguan Kecemasan Sosial Pattiasina, Timothy John; Ar Rosyid, Harits; Handayani, Anik Nur; Junaedi, Hartarto; Trianto, Edwin Meinardi
Jurnal Pekommas Vol 9 No 1 (2024): Juni 2024
Publisher : Sekolah Tinggi Multi Media “MMTC” Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56873/jpkm.v9i1.5317

Abstract

This literature review discusses efforts to enhance cognitive behavioral therapy in addressing social phobia, such as social anxiety disorder, by utilizing serious games and virtual reality exposure therapy. In the worldwide context of the COVID-19 outbreak, conventional cognitive behavioral therapy faces significant challenges, prompting practitioners and researchers to seek innovative e solutions. During the conducted literature review, several research articles were identified that explore the utilization of virtual reality exposure therapy and serious games within the stages of cognitive behavioral therapy. Using the PICOC method and software such as Publish or Perish, Zotero, and VOSViewer, 30 journal articles have been obtained, indicating that virtual reality exposure therapy and serious games can enhance the effectiveness of cognitive behavioral therapy. However, there are clear signs suggesting that integrating virtual reality (VR) technology and serious games on smartphones into the cognitive behavioral therapy process could offer a promising avenue for new research. This approach may help address the challenges brought about by the effects of the COVID-19 pandemic on people with social anxiety disorder, particularly in Indonesia. Although further research and therapy adaptation according to the cultural context in Indonesia are needed, this development offers new research opportunities as an alternative therapeutic approach with significant advancements in addressing social anxiety disorder.
YOLO-based object detection performance evaluation for automatic target aimbot in first-person shooter games Asmara, Rosa Andrie; Rahmat Samudra Anugrah, Muhammad; Wibowo, Dimas Wahyu; Arai, Kohei; Burhanuddin, Mohd Aboobaider; Handayani, Anik Nur; Damayanti, Farradila Ayu
Bulletin of Electrical Engineering and Informatics Vol 13, No 4: August 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v13i4.6895

Abstract

First-person shooter (FPS) focuses on first-person perspective action gameplay, with gunfights usually giving the player a choice of weapons, significantly impacting how the player approaches or strategies. General military-themed FPS games have realistic models with actual weapons’ shapes and characteristics. This type of game requires high aiming accuracy while using a mouse on a PC. However, not all players have a fast response time in knowing the surrounding situation. New players may need aid when targeting enemies in the FPS world. One popular yet underhanded method is injecting a program code using a dynamic-link library (DLL) to manipulate memory and asset data from the game. Instead of DLL, we promote a novel approach using the player’s real-time game screen, detecting the person without injecting program code into the game. The you only look once (YOLO) algorithm is used as an object detector model since it can process images in real time for up to 45 frames per second. The proposed object detection has an outstanding performance with 65% accuracy, 98% precision, and 61% recall of 51 tests for each game. YOLO’s fastest detection speed produces an average of 35 FPS on the YOLO tiny variant using a mixed precision (half) graphics processing unit (GPU).
Pengembangan oven pengering telur asin asap cair berbasis IoT Nur Handayani, Anik; Mutiara, Titi; Nurjanah, Nunung; Nur Rahma, Andika Bagus
Masyarakat Berdaya dan Inovasi Vol. 5 No. 1 (2024)
Publisher : Research and Social Study Institute

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33292/mayadani.v5i1.153

Abstract

Artikel ini bertujuan untuk memberikan gambaran pengembangan oven pengering untuk telur asin dengan asap cair, berbasis Internet of Thing (IoT) di SLB Autis Laboratorium UM. Metode pelaksanaan melalui observasi, pengembangan alat oven telur asin, forum grup discussion, dan sosialisasi alat. Sosialiasi dilaksanakan dengan tujuan memberi penyuluhan pembuatan telur asin dengan metoda asap cair, yang dilanjutkan dengan pengeringan menggunakan oven pengering. Hal ini dilakukan untuk mengembangkan oven yang sudah ada dengan metode oven asap. Kegiatan pengabdian ini dilaksanakan untuk memberikan pelatihan kepada para peserta didik disabilitas untuk melatih kemampuan mereka dalam bidang kewirausahaan, khususnya dalam pembuatan produk telur asin.
Hand image reading approach method to Indonesian Language Signing System (SIBI) using neural network and multi layer perseptron Bagaskoro, Muhammad Cahyo; Prasojo, Fadillah; Handayani, Anik Nur; Hitipeuw, Emanuel; Wibawa, Aji Prasetya; Liang, Yoeh Wen
Science in Information Technology Letters Vol 4, No 2 (2023): November 2023
Publisher : Association for Scientific Computing Electronics and Engineering (ASCEE)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31763/sitech.v4i2.1362

Abstract

Classification complexity is the main challenge in recognizing sign language through the use of computer vision to classify Indonesian Sign Language (SIBI) images automatically. It aims to facilitate communication between deaf or mute and non-deaf individuals, with the potential to increase social inclusion and accessibility for the disabled community. The comparison of algorithm performance in this research is between the neural network algorithm and multi-layer perceptron classification in letter recognition. This research uses two methods, namely a neural network and a multi-layer perceptron, to measure accuracy and precision in letter pattern recognition, which is expected to provide a foundation for the development of better sign language recognition technology in the future. The dataset used consists of 32,850 digital images of SIBI letters converted into alphabetic sign language parameters, which represent active signs. The developed system produces alphabet class labels and probabilities, which can be used as a reference for the development of more sophisticated sign language recognition models. In testing using the neural network method, good discrimination results were obtained with precision, recall and accuracy of around ±81%, while in testing using the multi-layer perceptron method around ±86%, showing the applicative potential of both methods in the context of sign language recognition. Testing of the two normalization methods was carried out four times with comparison of the normalized data, which can provide further insight into the effectiveness and reliability of the normalization technique in improving the performance of sign language recognition systems.
Water quality identification based on remote sensing image in industrial waste disposal using convolutional neural networks Widiharso, Prasetya; Handoko, Wahyu Tri; Wibawa, Aji Prasetya; Handayani, Anik Nur; Teng, Ming Foey
Science in Information Technology Letters Vol 2, No 2: November 2021
Publisher : Association for Scientific Computing Electronics and Engineering (ASCEE)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31763/sitech.v2i2.638

Abstract

Measuring the quality of river water used as industrial wastewater disposal is needed to maintain water quality from pollution. The chemical industry produces hazardous waste containing toxic materials and heavy metals. At specific concentrations, industrial waste can result in bacteriological contamination and excessive nutrient load (eutrophication). Using the Convolutional Neural Network (CNN), the method for measuring water quality processes remote sensing images taken via an RGB camera on an Unmanned Aerial Vehicle (UAV). The parameter measured is the change in the color of the river water image caused by the chemical reaction of the heavy metal content of industrial waste disposal. The test results of the Convolutional Neural Network (CNN) method in 2.01s/step obtained the value of training loss mode 17.86%, training accuracy 90.62%, validation loss 23.43%, validation accuracy 83.33%.
Decision tree based algorithms for Indonesian Language Sign System (SIBI) recognition Nugraha, Agil Zaidan; Salsabila, Reni Fatrisna; Handayani, Anik Nur; Wibawa, Aji Prasetya; Hitipeuw, Emanuel; Arai, Kohei
Applied Engineering and Technology Vol 3, No 2 (2024): August 2024
Publisher : ASCEE

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31763/aet.v3i2.1536

Abstract

Indonesian Sign Language System (SIBI) recognition plays a crucial role in improving effective communication for individuals with hearing loss in Indonesia. To support automatic SIBI recognition, this research presents a performance analysis of two main algorithms, namely Decision Tree and C4.5, in the context of the SIBI recognition task. This research utilizes a rich SIBI dataset that includes a variety of SIBI signs used in everyday communication. Data pre-processing, model construction with both algorithms, and model performance evaluation using accuracy, precision, recall, and F1-score metrics are all part of the study. Regarding SIBI recognition accuracy, the experimental results demonstrate that the Decision Tree performs better than Decision Tree. The Decision Tree also makes models that are easier to understand, which is important for making communication systems based on SIBI.
Co-Authors A.N. Afandi Abdullah Iskandar Syah Achmad Hamdan Achmad Safii Achmad Safi’i Achmad Safi’i Adi Izhar Bin Che Ani Adi Prastowo, Nur Kodrad Adib Nur Sasongko Adim Firmansah Afandi, Farrel Candra Winata AFIF, ACHMAD Agung Bella Putra Utama Agusta Rakhmat Taufani Ahmad Dardiri Ahmad Kholish Fauzan Shobiry Ahmad Munjin Nasih Ahmad Nurdiansyah Ahmad Sahru Romadhon Aji Prasetya Wibawa Alifia Fitri Wahyudi Amaliya, Sholikhatul Andrew Nafalski Anita Qotrun Nada Anusua Ghosh Aqdam, Yutsabitul Ardiansyah, Lucky Arengga, Danang Ari Priharta Ari Priharta Arif Widodo, Baskoro Aripriharta Aripriharta - Ariyanta, Nadindra Dwi Asfani, Khoirudin Atmaja, Muhammad Bayu Setya Wahyu Ayu Puspita Azhryl Assagaf Aziz, Faiz Syaikhoni Azizah, Desi Fatkhi Bagaskoro, Muhammad Cahyo Baihaqi, Dimas Imam Baihaqi, Dimas Imam Baskoro Arif Widodo Bayu Prasetyo Bayu Prasetyo, Bayu Bin Che Ani, Adi Izhar Burhanuddin, Mohd Aboobaider Chalista Yulia Hazizah Chandrika, Katya Lindi Chuttur, Mohammad Yasser Damanhuri, Nor Salwa Damayanti, Farradila Ayu Damayanti, Masyita Danang Arengga Danang Arengga Wibowo Dedes, Khen Desi Fatkhi Azizah Devita Maulina Putri, Devita Maulina Dewi Aprilia Lintang Dhiyaurrahman Fakhruddin Didik Dwi Prasetya Difa Hananta Firdaus Am Dika Fikri L Dimas Wahyu Wibowo Dityo Kreshna Argeshwara Dityo Kreshna Argeshwara Dolly Indra Dwi Prihanto Dyah Lestari Dyah Rosita Anggraeni Edinar Valiant Hawali Edwin Meinardi Trianto Eka Rahayu Setyaningsih Eko Noerhayati Erwina Nurul Azizah Evania Yafie F.ti Ayyu Sayyidul Laily Faiz Syaikhoni Aziz Faqih, Kamil Faradhila Saffa Dhamira Farah Nisa’ Salsabila Fauzi, Juwita Annisa Fauzi, Rochmad Felix Andika Dwiyanto Ferina Ayu Pusparani Fidyah Ajeng Wulandari Fukuda, Osamu Gavyn Rafael Davasco Gianika Roman Sosa Graciello, Manuel Tanbica Gunawan Budi P Guyub Raharjo Gwo-Jiun Horng Haffas Zikri Ariyandi Hakkun Elmunsyah Halimahtus Mukminna, Halimahtus Harits Ar Rasyid Harits Ar Rosyid Hariyono Hariyono Hartarto Junaedi Hary Suswanto Heru Herwanto Heru Wahyu Herwanto Hirashima, Tsukasa Hitipeuw, Emanuel Hosen, Moh I Made Wirawan Ida Ayu Putu Sri Widnyani Ihsan Al-Fikri Imam Tree Utomo Imanuel Hitipeuw Ira Kumalasari Irfan Ramadhani Irham Fadlika Jehad A. H. Hammad Jehad A.H. Hammad Jevri Tri Ardiansah Jevri Tri Ardiansah Julfikar Mawansyah Kamil Faqih Kartika Candra Kirana Kartika Kirana Kasmira, Kasmira Katya Lindi Chandrika Khurin Nabila Kinasih, Agnes Nola Sekar Kirom, M Kohei Arai Kohei Arai Kohei Arai Kohei Arai Korba, Petr Kurniawan, Wendy Cahya Kusumawardana, Arya Laili, Mery Nur Laily, F.ti Ayyu Sayyidul Laistulloh, Dika Fikri Lalu Ganda Rady Putra Langlang Gumilar Larasati, Jade Rosida Leonel Hernandez, Leonel Lestari , Widya Liang, Yeoh Wen Liang, Yoeh Wen lilis nurhayati M. Adib Nursasongko M. Nuzuluddin M. Rodhi Faiz M. Rodhi Faiz Machumu, Paul Igunda Made Ayu Dusea Widyadara Made Ayu Dusea Widyadara - Universitas Nusantara Kediri, Made Ayu Dusea Widyadara Mahamad, Abd Kadir Manga, Abdul Rachman Maqbullah, Afwatul Marga Asta Jaya Mulya Maula Zikri Renaldi Ming Foey Teng, Ming Foey Moch Haris Purwanto Moh Zainul Falah Moh. Zainul Falah Mohammad Agung Rizki Mohammad Muzayyin Amrulloh Mohammad Rizky Kurniawan Mohammad Yussril Asri Mohsen Samadi Mokh Sholihul Hadi Much. Arafat Al Mubarok Muchamad Wahyu Prasetyo Muchamad Wahyu Prasetyo Muhamad Arifin Muhamad Arifin, Muhamad Muhammad Alfan Muhammad Arifin Muhammad Hafiizh Muhammad Holqi Rizki Azhari Muhammad Iqbal Akbar Muhammad Jauharul Fuady Muhammad Ridwan Muhammad Ulinnuha Musthofa Muhammad Younas Darvish Muhammad Zaki Wiryawan Muhammad Zaky Rahmatsyah Muladi Mumtaazah, Muhammad Athar Mutiara, Titi Nadindra Dwi Ariyanta Nailah Aliya Putri Nandang Mufti Nastiti Susetyo Fanani Putri Nastiti Susetyo Fanani Putri Nastiti Susetyo Fanany Putri Naufal Rizaldi Gunawan Nisa, Khoirotun Nizaar, Roub Nor Salwa Damanhuri Norma Mustika, Soraya Norzanah Rosmin Norzanah Rosmin Nugraha, Agil Zaidan Nugraha, Youngga Rega Nunung Nurjanah Nur Eva Nur Halim Nur Rahma, Andika Bagus Nurul Rismayanti Nurus Sihab Aminudin Nuzuluddin, M. Osamu Fukuda Panji Ageng Timor Pamungkas Prasetya Widiharso Prasetya Widiharso Prasojo, Fadillah Pratama, Awanda Setya Sanfajar Pratama, Diaz Octa Priharta, Ari Primadi, Wahyu Purnomo, Purnomo Putra Utama, Agung Bella Putri Galuh Ningtiaz Qomaria, Ulfa Rafli Indar Praja Rahman, Nukleon Jefri Nur Rahmat Samudra Anugrah, Muhammad Ramadhan, Aslan Poetra Ramadhani, Lolita Resty Wulanningrum Reza Setyawan Ria Febrianti Rini Nur Hasanah Rochmawati Rochmawati Rochmawati Rochmawati Romadlon, Muhammad Rizqi Rosa Andrie Asmara Rosyidin, Zulkham Umar Rusdha Aulia Salah Abdullah Khalil Abdulrahman Salsabila, Reni Fatrisna Saodah Omar Selly Handik Pratiwi Seno Isbiyantoro Setyaningsih, Eka Rahayu Sevilla, Felix Rafael Segundo Siti Sendari Slamet Wahyudi Slamet Wibawanto Soraya Norma Mustika Soubin Sisavath Srini Suciati, Reski Dwi Suryani, Ani Wilujeng Suti Mega Nur Azizah Suziyani Mohamed Syaad Patmantara Syaad Patmanthara Syaghlu Natsalam Saputra Syaichul Fitrian Akbar Syamsul Bahri Taiga Haruta Taw, Phillip Teguh Andriyanto, Teguh Timothy John Pattiasina Titaley, Gilberth Valentino Tony Yu Tran Thi Hao Triyanna Widiyaningtyas Tsukasa Hirashima Urnika Mudhifatul Jannah Utama, Agung Bella Putra Utomo Pujianto Veithzal Rivai Zainal Wahyu Arbianda Yudha Pratama Wahyu Irianto Wahyu Nur Hidayat Wahyu Primadi Wahyu Sakti Gunawan Irianto Wahyu Styo Pratama Wahyu Tri Handoko Wibawa, Aji Presetya Wibowo, Kusmayanto Hadi Wicaksana, Ardi Anugerah Widiharso, Prasetya Wijaya, Mikel Ega Wirawan, Muhammad Zaki Wiryawan, Muhammad Zaki Yogi Dwi Mahandi Yosi Kristian Yu, Tony Yudha Islami Sulistya Yuliana Melita Pranoto Yuni Rahmawati Yusuf Tri Hadi Mulyana Zaeni, Ilham Ari Elbaith Zufida Kharirotul Umma Zulkham Umar Rosyidin Zulkham Umar Rosyidin Zulkifli, Shamsul Aizam